a chance-constrained economic dispatch model in wind-thermal-energy storage system
Clicks: 232
ID: 159304
2017
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
232 views
42 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #223 of 526 articles by views in acs combinatorial science
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 526 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs) to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED) model for the wind-thermal-energy storage system (WTESS) is developed in this paper. An optimization model with the wind power and the energy storage system (ESS) is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG). A Gaussian mixture model (GMM) distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS) is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.
| Reference Key |
hu2017energiesa
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Yanzhe Hu;Yang Li;Mengjie Xu;Li Zhou;Mingjian Cui |
| Journal | acs combinatorial science |
| Year | 2017 |
| DOI |
10.3390/en10030326
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.